1. Field of the Application
This application relates generally to test and diagnostic systems for machines or other operating equipment. More particularly, the application relates to an automated process for optimizing diagnostic trees. While the application is described in the context of a vehicle diagnostic system and method, the principles of the present application are equally applicable for air conditioning testing and servicing systems, wheel systems, as well as for various non-automotive apparatus.
2. Description of the Related Art
Automotive vehicles are becoming highly computerized products. Consequently, a number of different types of diagnostic tools have been used to assist in diagnosis and repair of fault conditions in automotive vehicles. Such diagnostic tools can typically be connected to an on-board computer of a vehicle in order to download and analyze vehicle operational information from the on-board computer. For example, a diagnostic tool may obtain information about a vehicle's engine, transmission, mechanical systems, air conditioning systems, braking system, power system, or any other system.
Automotive mechanics are increasingly relying upon computerized diagnosis of vehicle operational information that can be accessed via a vehicle on-board computer to diagnose and repair vehicle faults. This information is often in the form of diagnostic trees, which are created by Original Equipment Manufacturers (OEMs). Diagnostic tools typically allow a user to enter information, including fault symptoms, into the diagnostic tool to be used instead of or in conjunction with the information downloaded from the vehicle's on-board computer to diagnose and assist in the repair of fault conditions in the vehicle.
A number of different types of diagnostic tools have been used, such as engine analyzers, which are designed to monitor a variety of operating conditions of an internal combustion engine, and scanners for downloading data from vehicle on-board computers. In addition, diagnostic tools may include laboratory-type tools like oscilloscopes, digital volt-Ohm meters (DVOM) and the like.
These diagnostic tools may be used with a computer based diagnostic platform that permits a fault-based drivability diagnosis of a vehicle. The platform may present a user with a menu of problems indicated, e.g., by symptoms or service codes, and the user selects those problems that are pertinent to the vehicle under test. Based upon the selected faults, the system presents the user with a list of tests to be performed to diagnose the cause or causes of the faults. The tests can be listed in the order in which they would most likely be effective in diagnosing the vehicle faults, based upon manufacturer's information and previous repair and diagnosis experience with this type of vehicle, for example.
Manufacturers create diagnostic trees to illustrate the tests for their vehicles on an annual basis, such as for individual Year/Make/Model combinations. The menu of problems and diagnostic trees can include a standard list of symptoms to be used for vehicles since vehicles use common technology. For example, vehicles have mechanical, ignition, fuel, and computer components that function in roughly the same manner. A standard list of symptoms is used because it provides a consistent interface and diagnostic philosophy for these vehicles, and promotes technician and service writer familiarization. Other more specific symptoms can then be assigned to specific vehicles for which particular problems are known to exist.
In developing test procedures, expert automotive technicians may evaluate individual symptoms for each specific vehicle. Based on their experience, they develop a list of causes for each symptom and determine a test procedure the user should perform for each cause. The experts attempt to cover diagnostic trouble codes that could be set by each specific automotive vehicle. As a result, an expert technician will manually prepare automotive diagnostic code tips within the diagnostic trees, repair procedures, component operations, testing processes and other similar functions for possible vehicle problems and this information can then be displayed in a diagnostic tool. However, the experts then spend much time preparing many hypothetical repair processes that may not be used because many of the problems do not occur. It is estimated that more than 80% of this information is not used, read, or selected by a technician. This information is still necessary, though, because technicians need to be prepared for all problems.
In addition, many diagnostic trees are identical or similar in content and structure from year to year. However, each tree for a new model should still be evaluated by a Subject Matter Expert (SME) to determine if the existing knowledge (e.g., diagnostic code tips) for a specific vehicle applies to the new model or a similar vehicle in part or in total. This process can take a significant amount of time and effort, and is repetitive for SMEs, which assist in the evaluation of many other diagnostic systems and data.
Furthermore, the manufacturer's diagnostic trees are written assuming the availability of specific equipment. Technicians that do not have the equipment specified may not be able to follow the diagnostic trees for symptom resolution. Therefore, while reviewing diagnostic tress, SMEs may substitute methods in a tree with alternate methods for obtaining the same information, which can make the diagnostic tree more accessible to a greater number of technicians. The SMEs usually go through each tree and type the changes by hand, which again takes a significant amount of time and effort.
There is, therefore, a general need for an automated system for incorporating similar information and/or changes from one diagnostic tree to another.